Quantitative X-ray tomography of advanced polymer composites

Advanced composite materials (ACMs) typically contain two or more constituents, such as resin, fibers, and pores, with different physical and chemical characteristics. When combined, they produce a material with unique properties in terms of weight, strength, stiffness, or corrosion resistance.

To inspect and study their 3D internal structure in a non-destructive way, the ACMs are imaged with X-rays, after which a 3D image is reconstructed from the X-ray radiographs, and further processed and analyzed in multiple sequential steps. This conventional workflow, however, suffers from inaccurate modeling and error propagation which severely limits the accuracy with which ACM parameters of interest can be estimated.

In this project, we will develop a paradigm shifting approach in which the quantification of ACM parameters is substantially improved. This will be realized in a novel workflow by
1) accounting for possible deformation of the ACM during scanning, thereby reducing image reconstruction artefacts;
2) accurately modelling all constituents of the ACM (matrix, pores, and fibers);
3) directly estimating the ACM model parameters from the X-ray radiographs, thereby preventing error propagation by providing a feedback mechanism;
4) analyzing the workflow’s parameter space with respect to sensitivity and stability of parameters of interest.